The Experts below are selected from a list of 309 Experts worldwide ranked by ideXlab platform

Mouldi Bedda - One of the best experts on this subject based on the ideXlab platform.

  • Wireless voice command system based on Kalman filter and HMM models to control Manipulator Arm
    2009 4th International Design and Test Workshop (IDT), 2009
    Co-Authors: Attoui Hamza, Mohamed Fezari, Mouldi Bedda
    Abstract:

    The aim of this work is to implement on real-time a speech recognition module in order to control the movements of a five degree of freedom Manipulator Arm using a Kalman filter as a selector in noisy environment and HHM model to recognise 12 Arabic spotted words. The methodology adopted is based on detecting and spotting vocabulary words within a phrase generated by user, the system recognises the spotted words using Kalman filter to select these spotted words then a robust HMM (Hidden Markove Model) technique with cepstral coefficients to improve the recognition rate. To implement the approach on a real-time application, a Personal Computer parallel port interface was designed to control the movement of a set of stepper motors. The user can control the movements of five degree of freedom (DOF) for a robot Arm using a vocal phrase containing spotted words.

  • Wireless voice command system based on Kalman filter and HMM models to control Manipulator Arm
    2009 4th International Design and Test Workshop (IDT), 2009
    Co-Authors: Attoui Hamza, Mohamed Fezari, Mouldi Bedda
    Abstract:

    The aim of this work is to implement on real-time a speech recognition module in order to control the movements of a five degree of freedom Manipulator Arm using a Kalman filter as a selector in noisy environment and HHM model to recognise 12 Arabic spotted words. The methodology adopted is based on detecting and spotting vocabulary words within a phrase generated by user, the system recognises the spotted words using Kalman filter to select these spotted words then a robust HMM (hidden Markov model) technique with cepstral coefficients to improve the recognition rate. To implement the approach on a real-time application, a personal computer parallel port interface was designed to control the movement of a set of stepper motors. The user can control the movements of five degree of freedom (DOF) for a robot Arm using a vocal phrase containing spotted words.

Florian Cordes - One of the best experts on this subject based on the ideXlab platform.

  • ROBIO - Evolutionary development of an optimized Manipulator Arm morphology for manipulation and rover locomotion
    2011 IEEE International Conference on Robotics and Biomimetics, 2011
    Co-Authors: Alexander Dettmann, Malte Roemmermann, Florian Cordes
    Abstract:

    The planetary exploration rover Sherpa is equipped with a Manipulator Arm used for handling payload items as well as for improving its locomotive abilities. Due to the high weight of Sherpa of approx. 200kg and the maximum weight of a payload item of 5 kg, both applications need high torques. In addition, a dextrous operating space is needed which has to allow ground contact and the placement of payload items on pre-defined positions on the rover itself. In this paper we describe an optimization method which evolves a Manipulator Arm morphology that requires minimal torques to accomplish these to some extent conflictive applications. Covariance Matrix Adaptation Evolution Strategy in parallel processing is used to optimize the link lengths of the Manipulator Arm. A real-time simulation is used to model the rover, all constraints, and to evaluate each morphology by analyzing the required torques for accomplishing pre-defined tasks. The paper presents the simulation results and the final Manipulator Arm morphology.

  • Evolutionary development of an optimized Manipulator Arm morphology for manipulation and rover locomotion
    2011 IEEE International Conference on Robotics and Biomimetics, 2011
    Co-Authors: Alexander Dettmann, Malte Roemmermann, Florian Cordes
    Abstract:

    The planetary exploration rover Sherpa is equipped with a Manipulator Arm used for handling payload items as well as for improving its locomotive abilities. Due to the high weight of Sherpa of approx. 200kg and the maximum weight of a payload item of 5 kg, both applications need high torques. In addition, a dextrous operating space is needed which has to allow ground contact and the placement of payload items on pre-defined positions on the rover itself. In this paper we describe an optimization method which evolves a Manipulator Arm morphology that requires minimal torques to accomplish these to some extent conflictive applications. Covariance Matrix Adaptation Evolution Strategy in parallel processing is used to optimize the link lengths of the Manipulator Arm. A real-time simulation is used to model the rover, all constraints, and to evaluate each morphology by analyzing the required torques for accomplishing pre-defined tasks. The paper presents the simulation results and the final Manipulator Arm morphology.

C. Askew - One of the best experts on this subject based on the ideXlab platform.

  • Neural network-assisted variable structure control scheme for control of a flexible Manipulator Arm
    Automatica, 1997
    Co-Authors: M.k. Sundareshan, C. Askew
    Abstract:

    Complexities in controller designs for flexible Manipulators, mainly arising from the nonlinear vibrational dynamics, get further compounded when task executions are to be completed in the face of changing payloads. The development of a neural network-based scheme for adaptively implementing a variable structure controller to drive a flexible Manipulator Arm is described in this paper. The controller provides a satisfactory suppression of the tip vibrations while facilitating a rapid hub rotation for executing motions during which payload variations can occur. An efficient integration of the operational strong features of a trained neural network and a variable structure controller is made in the development of the overall control scheme. On the one hand, the high degree of inherent robustness of the variable structure control serves to reduce the architectural and training complexity of the neural network, while on the other, the faster processing capability of the neural network is exploited for on-line payload identification and adaptive implementation of the variable structure controller. The resulting control strategy is novel in facilitating a trained neural network to function synergistically with an established control scheme (viz. variable structure control) and is significantly different from the popularly discussed approaches for using neural networks for controller designs which mainly attempt to provide a neural network alternative to well established control schemes.

  • Neural network-based payload adaptive variable structure control of a flexible Manipulator Arm
    Proceedings of 1994 IEEE International Conference on Neural Networks (ICNN'94), 1994
    Co-Authors: M.k. Sundareshan, C. Askew
    Abstract:

    Complexities in controller designs for flexible Manipulators, mainly arising from the nonlinear vibrational dynamics, get further compounded when task executions are to be completed in the face of changing payloads. The development of a neural network-based scheme for adaptively implementing a variable structure controller (VSC) to drive a flexible Manipulator Arm is described in this paper. The controller design is novel and ensures a satisfactory suppression of the tip vibrations while facilitating a rapid hub rotation for executing motions during which payload variations can occur. An efficient integration of the operational strong features of a trained neural network and a VSC is made in the development of the overall control scheme.

Mohamed Fezari - One of the best experts on this subject based on the ideXlab platform.

  • Speech as a high level control for teleoperated Manipulator Arm
    2010 2nd International Conference on Advanced Computer Control, 2010
    Co-Authors: Ibrahiem M. M. El-emary, Mohamed Fezari, Hadj Ahmed Abbassi
    Abstract:

    In this work a tele-operated system for a robot Arm is designed and controlled by the operator, in witch voice control mode occur to carry out remote tasks. A voice command system for the Manipulator Arm is implemented as a high level control design and compared to a low level control design based on joystick. The high level control paradigm adopted is based on a spotted words recognition system using stochastic model, robust HMM (Hidden Markov Model) with Cepstral coefficients as parameters witch is used in automatic speech recognition system. To implement the approach on a real-time application, a Personal Computer USB interface was designed to transmit commands via Bluetooth components to control the movement of a Robot Arm (the TR-45). The user can control the movements of four degree of freedom (DOF) for TR-45 using a vocal phrase containing spotted words or using a joystick.

  • Wireless voice command system based on Kalman filter and HMM models to control Manipulator Arm
    2009 4th International Design and Test Workshop (IDT), 2009
    Co-Authors: Attoui Hamza, Mohamed Fezari, Mouldi Bedda
    Abstract:

    The aim of this work is to implement on real-time a speech recognition module in order to control the movements of a five degree of freedom Manipulator Arm using a Kalman filter as a selector in noisy environment and HHM model to recognise 12 Arabic spotted words. The methodology adopted is based on detecting and spotting vocabulary words within a phrase generated by user, the system recognises the spotted words using Kalman filter to select these spotted words then a robust HMM (Hidden Markove Model) technique with cepstral coefficients to improve the recognition rate. To implement the approach on a real-time application, a Personal Computer parallel port interface was designed to control the movement of a set of stepper motors. The user can control the movements of five degree of freedom (DOF) for a robot Arm using a vocal phrase containing spotted words.

  • Wireless voice command system based on Kalman filter and HMM models to control Manipulator Arm
    2009 4th International Design and Test Workshop (IDT), 2009
    Co-Authors: Attoui Hamza, Mohamed Fezari, Mouldi Bedda
    Abstract:

    The aim of this work is to implement on real-time a speech recognition module in order to control the movements of a five degree of freedom Manipulator Arm using a Kalman filter as a selector in noisy environment and HHM model to recognise 12 Arabic spotted words. The methodology adopted is based on detecting and spotting vocabulary words within a phrase generated by user, the system recognises the spotted words using Kalman filter to select these spotted words then a robust HMM (hidden Markov model) technique with cepstral coefficients to improve the recognition rate. To implement the approach on a real-time application, a personal computer parallel port interface was designed to control the movement of a set of stepper motors. The user can control the movements of five degree of freedom (DOF) for a robot Arm using a vocal phrase containing spotted words.

Pinhas Ben-tzvi - One of the best experts on this subject based on the ideXlab platform.

  • IROS - Experimental validation of a hybrid mobile robot mechanism with interchangeable locomotion and manipulation
    2009 IEEE RSJ International Conference on Intelligent Robots and Systems, 2009
    Co-Authors: Pinhas Ben-tzvi
    Abstract:

    This video submission presents the experimental validation and testing of a novel Hybrid Mobile Robot (HMR) system design using a complete physical prototype. The HMR consists of a combination of parallel and serially connected links resulting in a hybrid mechanism that consists of a locomotion platform and a Manipulator Arm for manipulation, both interchangeable functionally. The new design has the ability to interchangeably provide locomotion and manipulation capability, both simultaneously. This was accomplished by integrating the locomotion mechanism and the Manipulator Arm mechanism as one entity rather than two separate and attached mechanisms. The Manipulator Arm can be used as part of the locomotion platform and vice versa. The video demonstrates how this paradigm significantly enhances mobile robot functionality for locomotion and manipulation tasks.

  • Experimental validation of a hybrid mobile robot mechanism with interchangeable locomotion and manipulation
    2009 IEEE RSJ International Conference on Intelligent Robots and Systems, 2009
    Co-Authors: Pinhas Ben-tzvi
    Abstract:

    This video submission presents the experimental validation and testing of a novel hybrid mobile robot (HMR) system design using a complete physical prototype. The HMR consists of a combination of parallel and serially connected links resulting in a hybrid mechanism that consists of a locomotion platform and a Manipulator Arm for manipulation, both interchangeable functionally. The new design has the ability to interchangeably provide locomotion and manipulation capability, both simultaneously. This was accomplished by integrating the locomotion mechanism and the Manipulator Arm mechanism as one entity rather than two separate and attached mechanisms. The Manipulator Arm can be used as part of the locomotion platform and vice versa. The video demonstrates how this paradigm significantly enhances mobile robot functionality for locomotion and manipulation tasks.